End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: whatsapp-group-classifierv2
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# whatsapp-group-classifierv2
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4619
+- Accuracy: 0.8283
+- Precision: 0.8483
+- Recall: 0.8347
+- F1: 0.8407
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 4e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.9676        | 1.0   | 513  | 0.7151          | 0.7322   | 0.7315    | 0.7148 | 0.7182 |
+| 0.6846        | 2.0   | 1026 | 0.5747          | 0.7741   | 0.7918    | 0.7716 | 0.7732 |
+| 0.5657        | 3.0   | 1539 | 0.5265          | 0.7946   | 0.8224    | 0.7882 | 0.7983 |
+| 0.5294        | 4.0   | 2052 | 0.4870          | 0.8059   | 0.8260    | 0.8084 | 0.8163 |
+| 0.4941        | 5.0   | 2565 | 0.4787          | 0.8102   | 0.8326    | 0.8122 | 0.8210 |
+| 0.4956        | 6.0   | 3078 | 0.4796          | 0.8156   | 0.8363    | 0.8183 | 0.8252 |
+| 0.4701        | 7.0   | 3591 | 0.4812          | 0.8146   | 0.8370    | 0.8165 | 0.8230 |
+| 0.4521        | 8.0   | 4104 | 0.4738          | 0.8220   | 0.8398    | 0.8287 | 0.8336 |
+| 0.444         | 9.0   | 4617 | 0.4664          | 0.8195   | 0.8412    | 0.8240 | 0.8313 |
+| 0.4336        | 10.0  | 5130 | 0.4682          | 0.8244   | 0.8445    | 0.8311 | 0.8370 |
+| 0.4345        | 11.0  | 5643 | 0.4653          | 0.8229   | 0.8446    | 0.8285 | 0.8351 |
+| 0.4275        | 12.0  | 6156 | 0.4619          | 0.8254   | 0.8463    | 0.8322 | 0.8382 |
+| 0.4155        | 13.0  | 6669 | 0.4620          | 0.8288   | 0.8487    | 0.8356 | 0.8414 |
+| 0.4179        | 14.0  | 7182 | 0.4624          | 0.8283   | 0.8485    | 0.8354 | 0.8412 |
+| 0.4078        | 15.0  | 7695 | 0.4619          | 0.8283   | 0.8483    | 0.8347 | 0.8407 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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